Systems and methods for identifying a source of radio frequency interference in a wireless network

ABSTRACT

An interference detection system in a network identifies a first wireless station that has experienced radio frequency (RF) interference from an unknown source on at least one physical resource block (PRB) and identifies one or more second wireless stations that have experienced similar interference on the at least one PRB. A plurality of estimated interference source locations are determined based at least on geographic locations of the first wireless station and the one or more second wireless stations. The plurality of estimated interference source locations are scored based on a comparison of estimate interference to observed interference at the one or more second wireless stations and a geographical map is generated based on the scored plurality of estimated interference source locations, wherein the geographical map includes indicia indicative of the relative scores of the plurality of estimated interference source locations.

BACKGROUND

Wireless telecommunications networks may operate on portions of theradio frequency (RF) spectrum. In some situations, interference may becaused in such a way that is detrimental to the performance of a givenwireless telecommunications network. For example, external interferencemay occur when a device external to the network site transmits a signalin a spectrum that overlaps the RF spectrum of the network. In someinstances, interference events are irregular, affecting sites on aparticular day of the week or specific business hours, which can make itdifficult to identify the cause or source of the interference.Furthermore, the conventional process for identifying a source ofinterference requires significant human capital and specializedequipment. For example, even after field engineers manage to determinethat an interference event is occurring or has occurred for a particularnetwork site, the engineers must physically canvass the area proximateto the network site with a directional antenna to identify fluctuationsof the interference levels until the source of the interference isidentified.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an overview of an environment in which systems andmethods consistent with embodiments are used;

FIG. 2 illustrates an example environment in which one or moreembodiments, described herein, may be implemented;

FIG. 3 is a block diagram illustrating example components of a computerdevice 400 according to one embodiment;

FIG. 4 is a flow diagram illustrating an example process for estimatinga location of an unknown interference source, consistent withimplementations described herein;

FIG. 5 is a graph of exemplary uplink radio power for a wireless stationon a per-physical resource block (PRB) basis;

FIG. 6 illustrates an exemplary main wireless station and a number ofneighboring wireless stations;

FIG. 7 is a flow diagram illustrating one implementation of a processfor identifying candidate interference source locations consistent withembodiments described herein;

FIG. 8 is a graphical depiction of an exemplary boundary selection forthe example of FIG. 6 ;

FIG. 9 illustrates an exemplary heat map based on the example of FIG. 6;

FIG. 10 is a view of a portion, of the map of FIG. 8 , illustratingsector boundaries for a wireless station; and

FIG. 11 is a flow diagram illustrating one implementation of a processfor sector analysis vector generation consistent with embodimentsdescribed herein.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following detailed description refers to the accompanying drawings.The same reference numbers in different drawings may identify the sameor similar elements. The following detailed description does not limitthe invention, which is defined by the claims.

Telecommunications service providers may operate wireless networks(e.g., cellular or other types of wireless networks) at a given set offrequencies (or frequency bands) of the Radio Frequency (RF) spectrum.While these frequencies are often licensed (e.g., by a governmentalagency and/or by some other authority) for exclusive use by one entityor operator, some bands may be shared by multiple different entities.For instance, a portion of the RF spectrum may be designated for “sharedaccess,” or a portion of the RF spectrum that was previously licensedfor access by one entity may be licensed for additional entities. Insituations where the same portion of the RF spectrum is licensed for useby multiple entities, the use of the portion of the RF spectrum by oneentity may negatively impact the use of that portion of the RF spectrumby other entities.

For example, and as shown in FIG. 1 , an entity may cause excessive RFinterference (referred to herein simply as “interference” or “noise”).In some cases, there may be multiple sources causing RF interference.For example, assume that a wireless network provider operates wirelessstations 100-1 to 100-2 within a particular frequency band, and thatwireless stations 100 service a user equipment device (UE) 105. Furtherassume that another device 110 (also referred to as broadcast source110), which is associated with another entity, also operates within thesame frequency band, and emits an RF interference signal into that bandbecause of intermodulation, excessive power, poor filter design, or forother reasons. Such third-party broadcast sources may negatively impactthe operation of wireless station 100 (and/or of UE device 105 thatcommunicate with wireless station 100, such as mobile telephones,Internet of Things (“IoT”) devices, Machine-to-Machine (“M2M”) devices,etc.), by introducing RF interference or noise. Because the broadcastsource is associated with an entity that is separate from the entitythat owns and operates wireless stations 100, it may be difficult tocoordinate the operation of wireless station 100 to account for theunexpected and unpredictable interference caused by the broadcastsource.

Consistent with implementations described herein, an interference sourcelocation determination tool may be provided to more quickly andaccurately identify a likely location of an interference source. Inparticular, interference may be determined based on a particularfrequency range within which it is occurring. Wireless stations 100 areconfigured to operate in accordance with various frequency bands andtime slots, arranged in physical resource blocks (PRBs). A PRB denotesthe most granular aspect of a wireless station's capabilities andincludes both a frequency component and a time component. As describedherein, interference may be experienced and analyzed on a per-PRB basis.

For example, as described herein, interference-indicating data, such asuplink power measurements data (i.e., uplink signal power) forparticular PRBs may be received and stored by the wireless stations 100.When a wireless station experiences external interference,interference-indicating data for the neighboring wireless stations areretrieved and analyzed to determine whether similar interference isperceived by any neighboring wireless stations. Once wireless stationsthat are not experiencing a similar external interference are filteredout, a heat map indicating a likely location(s) of the interferencesource may be generated.

For example, when an affected wireless station is 100 is identified(referred to herein as main wireless station 100-1), either autonomouslyby an interference detection system or via external (e.g., manual)reporting, other wireless stations 100 that are proximate (i.e.,geographic neighbors) to the main wireless station 100-1 are examinedfor similar interference experiences on a particular PRB or PRBsaffecting main wireless site 100-1.

Consistent with embodiments described herein, the likely location(s) maybe determined by calculating error, such as root mean square error(RMSE) by using Free Space Path Loss (FSPL) calculations based on anumber of interference source location guesses. The process isiteratively repeated until minimum values of FSPL are determined. Theheat map is generated based on the calculations for each of a number ofguessed locations. The generated heat map is provided to field engineersto assist in expediting manual identification of the interferencesource.

FIG. 2 illustrates an example environment in which one or moreembodiments, described herein may be implemented. As shown in FIG. 2 ,environment 200 may include radio access network (RAN) 205 that includesa plurality of wireless stations 100-1 to 100-x (collectively referredto as wireless stations 100 and individually referred to as wirelessstation 100), a wireless station database 210, an interference detectionsystem 215, an interference reporting system 220, and one or morenetworks 225. The number of devices and/or networks, illustrated in FIG.2 , is provided for explanatory purposes. In practice, environment 200may include additional, fewer, different, or a different arrangement ofdevices and/or networks than illustrated in FIG. 2 .

For example, while not shown, environment 200 may include devices thatfacilitate or enable communication between various components shown inenvironment 200, such as routers, modems, gateways, switches, hubs, etc.Alternatively, or additionally, one or more of the devices ofenvironment 200 may perform one or more functions described as beingperformed by another one or more of the devices of environments 200.Devices of environment 200 may interconnect with each other and/or otherdevices via wired connections, wireless connections, or a combination ofwired and wireless connections. In some implementations, devices ofenvironment 200 may be physically integrated in, and/or may bephysically attached to other devices of environment 200.

RAN 205 may include a wireless telecommunications network (e.g., aLong-Term Evolution (LTE) RAN, a Third Generation Partnership Project(3GPP) a Fifth Generation (5G) RAN, etc. As mentioned above, RAN 205 mayinclude one or more wireless stations 100, via which devices (e.g., userequipment (UE), such as mobile telephones, IoT devices, M2M devices,etc.) may communicate with one or more other elements of environment200. RAN 205 may communicate with such devices via an air interface. Forinstance, RAN 205 may receive traffic (e.g., voice call traffic, datatraffic, messaging traffic, signaling traffic, etc.) from a UE via theair interface, and may forward the traffic to network 225. Similarly,RAN 205 may receive traffic intended for a UE from network 225 and mayforward the traffic to the UE via the air interface. RAN 205 may operateat a set of frequencies (e.g., a set of licensed spectra). In someembodiments, one or more of the bands, at which RAN 205 operates, may beshared with an entity other than the entity that owns and/or operatesRAN 205.

Wireless station database 210 may include one or more devices (e.g., aserver device, or a collection of server devices) for storing wirelessstation-related information. For example, wireless station database 210may receive, store, and/or output information relating to variouswireless stations 100 in RAN 205. Such information may include, amongother data elements, identification information, geographic locationinformation, and performance information relating to performancecharacteristics of each wireless station 100.

Interference detection system 215 may include one or more devices (e.g.,a server device, or a collection of server devices) to determine likelylocations of interference sources. For example, interference detectionsystem 215 may identify likely locations of interference sourcesdetected in RAN 205. For example, as briefly described above,interference detection system 215 may generate geographic heat maps thatidentify the likely locations of sources of interference based on datacollected from wireless stations 100 within RAN 205. Consistent withembodiments described herein, the heat map may be generated based onstatistical minimization of free space loss calculations at variousgeographic locations proximate to affected wireless stations.Interference detection system 215 may further take administrative orcorrective actions when detecting unique sources of interference, asdescribed in greater detail below.

Interference reporting system 220 may include one or more devices (e.g.,a server device, or a collection of server devices) to perform one ormore functions described herein. For example, interference reportingsystem 220 may include messaging systems capable of generating and/orsending messages via network 225. The messages may be emails, textmessages, application-specific messages, and/or other types of messagesrelated to alerts that a heat map of possible interference sources hasbeen generated by interference detection system 215. Consistent withimplementations described herein, interference reporting system 220 mayforward or otherwise notify network personnel (e.g., field engineers)about the identified interference and the generated heat map for use inascertaining the source of the interference. Interference reportingsystem 220 may also maintain a history of interference determinationsfor use in determining patterns.

Network(s) 225 may include one or more wired and/or wireless networks.For example, network(s) 225 may include one or more core networks of alicensed wireless telecommunications system (e.g., an LTE core network,a 5G core network, etc.), an Internet Protocol (“IP”)-based PDN, a widearea network (“WAN”) such as the Internet, a private enterprise network,and/or one or more other networks. One or more of the devices ornetworks shown in FIG. 2 may communicate, through network(s) 225, witheach other and/or with other devices that are not shown in FIG. 2 .Network 225 may further include, or be connected to, one or more othernetworks, such as a public switched telephone network (“PSTN”), a publicland mobile network (“PLMN”), and/or another network.

FIG. 3 is a block diagram illustrating example components of a computerdevice 300 according to one embodiment. Wireless stations 100, wirelessstation database 210, interference detecting system 215, andinterference reporting system 220 may include or may be included withinone or more of computer device 300. As shown in FIG. 3 , computer device300 may include a bus 310, a processor 320, a memory 330, an inputdevice 340, an output device 350, and a communication interface 360.

Bus 310 includes a path that permits communication among the componentsof computer device 300. Processor 320 may include any type ofsingle-core processor, multi-core processor, microprocessor, latch-basedprocessor, and/or processing logic (or families of processors,microprocessors, and/or processing logics) that executes instructions.In other embodiments, processor 320 may include an application-specificintegrated circuit (ASIC), a field-programmable gate array (FPGA),and/or another type of integrated circuit or processing logic.

Memory 330 may include any type of dynamic storage device that may storeinformation and/or instructions, for execution by processor 320, and/orany type of non-volatile storage device that may store information foruse by processor 320. For example, memory 330 may include a randomaccess memory (RAM) or another type of dynamic storage device, aread-only memory (ROM) device or another type of static storage device,a content addressable memory (CAM), a magnetic and/or optical recordingmemory device and its corresponding drive (e.g., a hard disk drive,optical drive, etc.), and/or a removable form of memory, such as a flashmemory.

Input device 340 may allow an operator to input information into device300. Input device 340 may include, for example, a keyboard, a mouse, apen, a microphone, a remote control, an audio capture device, an imageand/or video capture device, a touch-screen display, and/or another typeof input device. In some embodiments, device 300 may be managed remotelyand may not include input device 340. In other words, device 300 may be“headless” and may not include a keyboard, for example.

Output device 350 may output information to an operator of device 300.Output device 350 may include a display, a printer, a speaker, and/oranother type of output device. For example, output device 350 mayinclude a display, which may include a liquid-crystal display (LCD) fordisplaying content to the customer. In some embodiments, device 300 maybe managed remotely and may not include output device 350. In otherwords, device 300 may be “headless” and may not include a display, forexample.

Communication interface 360 may include a transceiver that enablesdevice 300 to communicate with other devices and/or systems via wirelesscommunications (e.g., radio frequency, infrared, and/or visual optics,etc.), wired communications (e.g., conductive wire, twisted pair cable,coaxial cable, transmission line, fiber optic cable, and/or waveguide,etc.), or a combination of wireless and wired communications.Communication interface 360 may include a transmitter that convertsbaseband signals to RF signals and/or a receiver that converts RFsignals to baseband signals. Communication interface 360 may be coupledto one or more antennas/antenna arrays for transmitting and receiving RFsignals.

Communication interface 360 may include a logical component thatincludes input and/or output ports and/or other input and outputcomponents that facilitate the transmission of data to other devices.For example, communication interface 360 may include a network interfacecard (e.g., Ethernet card) for wired communications and/or a wirelessnetwork interface (e.g., a WiFi) card for wireless communications.Communication interface 360 may also include a universal serial bus(USB) port for communications over a cable, a Bluetooth wirelessinterface, a radio-frequency identification (RFID) interface, anear-field communications (NFC) wireless interface, and/or any othertype of interface that converts data from one form to another form.

Device 300 may perform various operations in response to processor 320executing software instructions contained in a computer-readable medium,such as memory 330. A computer-readable medium may be defined as anon-transitory memory device. A memory device may be implemented withina single physical memory device or spread across multiple physicalmemory devices. The software instructions may be read into memory 330from another computer-readable medium or from another device. Thesoftware instructions contained in memory 330 may cause processor 320 toperform processes described herein. Alternatively, hardwired circuitrymay be used in place of, or in combination with, software instructionsto implement processes described herein. Thus, implementations describedherein are not limited to any specific combination of hardware circuitryand software.

Although FIG. 3 shows exemplary components of device 300, in otherimplementations, device 300 may include fewer components, differentcomponents, additional components, or differently arranged componentsthan depicted in FIG. 3 . Further, in some embodiments, one or more ofthe components described above may be implemented as virtual components,such as virtual processors, virtual memory, virtual interfaces, etc.Additionally, or alternatively, one or more components of device 300 mayperform one or more tasks described as being performed by one or moreother components of device 300.

FIG. 4 illustrates an example process 400 for estimating a location ofan unknown interference source, consistent with implementationsdescribed herein. In some embodiments, process 400 may be performed byinterference detection system 215. In some embodiments, process 400 maybe performed by, or in conjunction with, one or more other devices orsystems, such as wireless station database 210, and/or interferencereporting system 220. FIG. 4 is described in conjunction with FIGS. 5-10. Some of these figures include graphs or other graphicalrepresentations of data, which may be generated by interferencedetection system 215. In some embodiments, the figures graphicallyillustrate calculations, aggregation, analysis, and/or other types ofoperations that may be performed by interference detection system 215.

Process 400 may include identifying one or more wireless stations thatare experiencing unexpected interference, particularly when compared tosurrounding wireless stations (block 405). Consistent with embodimentsdescribed herein, interference may be determined based on a particularfrequency range within which it is occurring. Wireless stations 100 areconfigured to operate in accordance with various frequency bands andtime slots, arranged in physical resource blocks (PRBs). A PRB denotesthe most granular aspect of a wireless station's capabilities andincludes both a frequency component and a time component. For long termevolution (LTE) wireless stations (e.g., eNodeB's) or 5G New Radio (5G)wireless stations (e.g., gNodeB's), each wireless station 100 may have aset number of PRBs across its available frequency spectrum, each ofwhich comprise approximately 180 KHz of bandwidth. Accordingly, for awireless station 100 operating in a 10 MHz band, the wireless stationwill generally include 50 PRBs, each having a discrete frequency andtime allocation. Thus, for a given sector (e.g., where “sector” refersto a particular geographic region, which may approximately or preciselycorrespond to the coverage area of a particular wireless station 100, ora set of wireless stations 100, of RAN 205) and over a given time window(e.g., one minute, one hour, one day, one week, etc.), the received(i.e., uplink) radio power, per PRB, may be measured or otherwiseretrieved.

For instance, FIG. 5 includes a graph that shows an example of uplinkradio power, on a per-PRB basis, at a given sector and within a giventime window. Each bar on the plot may indicate, in some embodiments, anaverage of the received uplink radio power measured over a time window.In some embodiments, the plot may indicate a different aspects of thereceived radio power (e.g., the maximum uplink radio power measured overthe time window, the minimum uplink radio power measured over the timewindow, etc.). As shown, the uplink radio power measured at PRB 6 andPRB 10, at the sector and over the time window, may be relatively high,as compared to the radio power at the other PRBs. The relatively highuplink radio power may indicate a likely interference event.

Consistent with implementations described herein, PRB uplink powermeasurements or other related measurements for wireless stations 100 maybe aggregated or otherwise maintained in wireless station database 210on a periodic basis, such as every minute, every 10 minutes, every hour,etc. For example, wireless stations 100 may be configured to reportvarious elements of performance metrics (i.e., key performanceindicators (KPIs)) on a periodic basis. The reported KPIs may includeuplink power measurements for each PRB in the wireless station 100.Interference detection system 215 may monitor the PRB uplink powermeasurements for each wireless station 100 and may determine instancesof likely interference based thereon. For example, continued disrupted(i.e., reduced) PRB uplink power measurements over a period of time maybe a strong indication of interference. In some embodiments, autonomoussystems, such as artificial intelligence or machine learning systems maybe implemented in interference detection system 215 to identifyinterference-experiencing wireless stations 100 based on the availablehistorical data. In other implementations, interference detection system215 may receive indications of interference experiencing wirelessstations 100 via a manual reporting system. For example, wirelessinterference detection system may receive a wireless station identifierand date/time of the interference from an operator.

When an affected wireless station is 100 is identified (e.g., wirelessstation 100-1), either autonomously by interference detection system 215or via external (e.g., manual) reporting, wireless stations 100 that areproximate (i.e., neighbors) to the identified wireless station 100-1(also referred to as the “main wireless station” 100-1) are examined forsimilar interference experiences (block 410). For example, interferencedetection system 215 may identify neighboring wireless stations 100within an initial distance from the main wireless site 100-1, based onthe geographic location of the main wireless site 100-1, the PRB(s) thatare experiencing the interference, and the timeframe(s) during which thePRB(s) experienced the interference. As described above, wirelessstation database 210 may include information regarding wireless stationsin RAN 205, such as location information (e.g., longitude and latitudeinformation) and performance metrics (e.g., PRB KPIs). Using thecollected information regarding wireless stations 100 in RAN 205,interference detection system 215 may ascertain the identities andlocations of neighboring wireless stations 100 that are experiencingsimilar interference during similar timeframes.

FIG. 6 illustrates the main wireless station 100-1 and a number ofneighboring wireless stations 100-2, 100-3, 100-4, 100-5, and 100-6.Assume that main wireless station 100-1 has experienced interferencefrom an unknown source during at least some point in time. Consistentwith embodiments described herein, performance data for neighboringwireless stations 100-2 to 100-6 that exhibit a similar interference,may be obtained.

In some implementations, wireless stations 100-2 to 100-6, which mayexperience interference may be determined in an expanding step-wisemanner based on a location from main wireless station 100-1. Forexample, interference on neighboring wireless stations 100 may beinitially determined for neighboring wireless stations that are withindistances of about 3-4 kilometers (km) from the initial or main wirelessstation 100-1. For example, as shown in FIG. 6 , wireless stations100-2, 100-4, and 100-5 are within the initial range. If none of thestations are in the initial range, the range may be expandedincrementally, until a maximum range is reached. For example, the rangemay be expanded in 2 km increments until at least one other neighbor isdetermined or a maximum of 10 km from the main wireless station 100-1 isreached, though other smaller or larger increments are contemplatedherein. Neighbors at the shortest distance are more likely to experiencethe same interference as the main site and also offer data for enablingbetter accuracy when generating a heat map.

Referring back to FIG. 4 , after identifying neighboring wirelessstations 100, wireless stations 100 that are experiencing similarinterference effects are determined (block 415). As described above,external interference typically affects a small number of PRBs at awireless station 100. To filter out wireless stations that are notexperiencing the same interference, the PRB interference-related KPIdata (e.g., uplink signal level values) for the candidate wirelessstations 100 for the same time period as the main wireless station hasdetected interference, are retrieved and compared to the correspondinginterference-related KPI data on the affected PRBs. For example, usinguplink signal levels as an interference-related KPI, values in a −115 dBto −120 dB range generally indicate a low interference signal. Incontrast, a high interference signal is usually indicated my uplinksignal level ranging from approximately −75 dB to −105 dB. It should benoted that these ranges may be different, depending on the environmentand traffic each wireless station is handling.

By way of example, assume main wireless station 100-1 has identified anuplink signal level of −90 dB on PRB 30 and an uplink signal level of−85 dB on PRB 20, as indications of possible interference at PRBs 20 and30. When identifying relevant neighbors, wireless stations having normal(e.g., −115 dB to −120 dB) uplink signals for PRBs 20 or 30 are excludedor filtered out, even if those wireless stations exhibit higher signalslevel on different PRBs. To focus the analysis on particularinterference signals, data that may indicate other possible interferencesignals or factors are excluded. For the following discussion, assumethat wireless stations 100-2, 100-4, and 100-6 are identified asexperiencing interference on the same PRBs during the same timeframe asmain wireless station 100-1.

After identifying neighboring wireless stations 100 as sites that mayhave experienced similar interference as main wireless station 100-1, ananalysis of the PRB data for those wireless stations is performed toidentify likely locations for the source of the interference (block420). For example, to determine candidate interference source locations,path loss calculations, such as free space path loss (FSPL) calculationsmay be performed for each of a plurality of location approximationsbased on the distance between the wireless station and the selectedlocation approximation, the RF frequency of the PRB under investigation,and the estimated or expected uplink signal value at the wirelessstation. Minimization calculations may be performed to increase theaccuracy of the obtained coordinates. For example, an indication of theaccuracy of the selected location approximation may be calculated foreach of the wireless stations experiencing interference based on theFSPL calculations and the actual observed uplink power signal level, andthe interference source location approximation may be iterativelyadjusted until further adjustment does not result in an increased levelof accuracy. Although FSPL is provided as an exemplary path losscalculation methodology, it should be understood that additional methodsof path loss determination may also be used, consistent withimplementations described herein.

FIG. 7 is a flow diagram illustrating one implementation of a process700 for determining candidate interference source locations consistentwith embodiments described herein. Process 700 may be performed byinterference detection system 215. However, in some embodiments, process700 may be performed by, or in conjunction with, one or more otherdevices or systems, such as wireless station database 210, and/orinterference reporting system 220.

Process 700 may include identifying the neighboring wireless station 100whose PRB data shows the highest interference (block 705). For clarity,the identified wireless station 100 may be referred to as the “strongestcorrelating station.” For example, using the information retrieved fromwireless station database 205, interference detection system 215 maycompare the uplink power levels for the particular timeframe underinvestigation for each of the wireless stations identified in block 410.As the result of the comparison, interference detection system 215 mayconclude that wireless station 100-1 is the strongest correlatingstation. The strongest correlating station may not be the main wirelessstation, since various factors may go into an initial identification ofan interference condition, for example the identification may be mademanually in response to customer complaints, effects on other networkequipment, diagnostics, etc.

Next, the geographic boundary for the likely interference sources isdetermined based on all possible combinations of the strongestcorrelating station with all other interference-affected neighbors(block 710), where each combination may correspond to a portion of theboundary. For example, if block 410 above identified threeinterference-affected wireless stations (100-1 (referred to as A), 100-2(referred to as B), 100-4 (referred to as C), and 100-6 (referred to asD)), with the strongest correlating station being wireless station A,the remaining combinations would include wireless station A-B, A-C, A-D,A-B-C, A-B-D, A-C-D, and A-B-C-D. FIG. 8 graphically depicts an exampleof such a boundary selection over the map of FIG. 6 . As shown, wirelessstations 100-1, 100-2, 100-4, and 100-6 form the vertices along theouter boundary 800 within which the interference source is likely to befound.

Next, an initial interference source location within the geographicboundary is selected (block 715). An exemplary location is depicted inFIG. 8 at location 810-1, within boundary 800. In some implementations,an initial location may be set equal to the location of the strongestcorrelating station, although any other location with boundary 600 maybe selected.

Using the selected location, expected interference-related KPI valuesfor each wireless station on each combination from the initiallyselected location are determined (block 720). For example, expecteduplink signal level values may be calculated using free space path lossas expressed by equations (1) and (2) below:d=10^((20 log) ¹⁰ ^((frequency)−SignalLevel−27.55)/20),  (1)where d is the distance between wireless station and the selectedlocation (in km), frequency refers to the RF frequency (in megahertz) ofthe PRB under investigation, SignalLevel refers to the estimated orexpected uplink signal value at the wireless station (in decibels), and27.55 is a constant relating to the spherical wave front of the RFsignal and the units selected for the computation (e.g., km and MHz) inthis example. The distances between the selected location and therespective wireless stations A-D are depicted as d_(A) to d_(D) in FIG.8 . Solving equation (1) for SignalLevel results in:SignalLevel=20 log₁₀(frequency)+20 log₁₀(d)−27.55  (2)

Once expected values for uplink signal levels have been calculated foreach wireless station 100, these values are compared to the observed oractual values to determine the accuracy of the selected location (block725). In one implementation, the comparison may include calculating rootmean squared error for each interference experiencing wireless station.The root mean squared error may be expressed as:RMSE=√{square root over ([Σ_(i=1)^(n)(Expected_(i)−Actual_(i))²)}/n],  (3)where n is the number of interference-experiencing wireless stations,expected is the uplink signal level calculated in equation (2), andactual is the observed uplink signal level at the time of theinterference, whose value was retrieved from wireless station database210 at block 410 above. A lower value for RMSE indicates that theexpected value is closer to the actual value over the range of data.Although RMSE is described as an accuracy determining methodologyherein, other statistical calculations for error may be used, such asmean square error (MSE), mean absolute scaled error (MASE), meanabsolute percentage error (MAPE), symmetric MAPE (SMAPE), etc.

A minimization process is performed for RMSE (block 730). For example,interference detection system 215 may iteratively select additionalestimated locations and calculate expected and RMSE values for eachlocation, until a minimum RMSE is obtained. Process 700 may result indetermining a number of locations and their corresponding RMSE values.

Returning to FIG. 4 , scores are generated for each of the identifiedlocations (block 425). For example, interference detection system 215determines a score for use in generating the heat map of possibleinterference source locations briefly described above. In one exemplaryimplementation, the scores may be based on the RMSE values as well as astatistical constant reflecting the number or count of wireless stationsthat are possibly experiencing the interference. For example, each scoremay be weighted 70% based on the number of wireless stations beinganalyzed and 30% based on the RMSE for the particular location.

Next, a heat map is generated based on the identified locations andtheir relative scores (block 430). For example, interference detectionsystem 215 generates a map that indicates the identified locations andprovides graphical indications of the probabilities that theinterference source is proximate to the identified locations.

FIG. 9 is an example of a heat map 900 generated using the process ofblock 420. As shown, heat map 900 includes a geographical map of theaffected locations and identifies the specific locations 810-1 through810-x. In addition, heat map 900 includes graphical indicia 905 based onthe relative scores and aggregate proximity for each location thatindicates a relative probability that the interference source would befound in a particular area. In some embodiments, as shown in FIG. 9 ,graphical indicia 905 may be provided as an overlay of varying color oropacity to indicate higher and lower probability.

The generated heat map may be used to ascertain the actual location ofthe interference source and to initiate remediation (block 435). Forexample, interference detection system 215 may provide or forward theheat map to interference reporting system 220 for delivery to relevantfield personnel or other entities associated with the service providerof RAN 205.

In the embodiments described above, sector azimuth (i.e., angle oforientation of the antenna) and beam width are not taken intoconsideration in identifying a possible interference source. This may bethe case for wireless stations that broadcast omnidirectional signalshaving a beam width of 360 degrees. However, in some circumstances,particular sectors of wireless stations may transmit signals indifferent, selected directions. To account for the antenna directions,the FSPL determined at block 420 may be adjusted by identifyingboundaries (e.g., polygons) for each one of the sectors for eachwireless station. The FSPL calculation may then be adjusted based onwhether a guessed location falls within the boundary for the particularsector. If the guessed location is within the boundary, no adjustmentsare necessary. However, if the point is not within the boundary, anadjustment is made to the FSPL calculation for the particular location.For example, a +3 dB adjustment may be made to reflect that theparticular wireless station is not detecting the interference directlywithin its transmission beam and detects a lower level of interferencethan the one calculated without the adjustment.

FIG. 10 illustrates a portion of FIG. 8 in which wireless station 100-1cover sectors 1000-1 to 1000-3. Sector 1000-2 is under investigation forthe PRBs discussed above and is shaded in gray. In this example, severalof locations 810 are not within the boundaries of sector 1000-2.Consistent with embodiments described herein, the FSPL calculations forthese guessed locations may be adjusted by +3 dB for each wirelessstation, for which the location falls outside of the sector boundary. Inthis way, lower interference values for locations outside of aparticular sector do not unnecessarily impact the RMSE minimizationprocess. The adjustments may result in more accurate locationdetermination.

In some instances, various portions of the heat map may have similarintensities (based on the scores generated in block 425 above),rendering it difficult to identify a particular field search startingpoint without field expertise or any additional information. Consistentwith embodiments described herein, a collocated sector analysis may beperformed to estimate a direction in which the interference source ismore likely to be located on a per-wireless station basis.

FIG. 11 illustrates an example process 1100 for determining a startingsearch location based on a collocated sector analysis. In someembodiments, process 1100 may be performed by interference detectionsystem 215. In some embodiments, process 1100 may be performed by, or inconjunction with, one or more other devices or systems, such as wirelessstation database 210, and/or interference reporting system 220. FIG. 11is described in conjunction with FIG. 12 .

In addition to, or in lieu of the heat map described above (e.g., heatmap 900), a cluster map may be generated (block 1105) that clusters topossible interference source locations based on a predetermined clusterdistance (e.g., 800 meters). Next, it is determined whether multipleclusters have been identified (block 1110). For example, based onK-means clustering, various clusters and related cluster centroids maybe generated. If optimized clustering results in a single cluster beingidentified (block 1110—NO), field searching may be targeted based on thecentroid of the identified cluster (block 1115). However, if multipleclusters are identified (block 1110—YES), an initial sector analysisvector may be generated for each wireless station 100 that isexperiencing similar interference effects (block 1120).

As described above in relation to FIG. 10 , each wireless station 100that is experiencing similar interference effects (as identified inblock 415 above) may have more than one sector pointing in differentdirections (azimuth) and with different beam widths. Taking this intoaccount, it can be assumed that, like the embodiment of FIG. 10 , anysector that is seeing the interference source directly (i.e., within itsazimuth and beam width) will most likely show a higher interferencepower level. Accordingly, for a site that has more than one sectoraffected by interference, a vector can be initially determined in thedirection of the most affected sector's azimuth (e.g., that sectorshowing the highest interference power level; also referred to as the“main” sector). In the example, of FIG. 10 , this vector 1050 (shown asa dashed line) would be directed along the azimuth angle of sector1000-2, which may be referred to as the main sector.

Next, consistent with implementations described herein, the angle of theinitial sector analysis vectors may be steered (i.e., adjusted) based onthe interference power levels on the collocated sectors (block 1125).For example, consider wireless station wireless station 100-1 havingsectors 1000-1 to 1000-3, as shown in FIG. 10 . As discussed above, eachsector 1000-1 to 1000-3 has a particular interference power reading fora particular PRB that is experiencing interference effects. A resultantvector 1055 may be generated based on the azimuth, beam width, andinterference power level in the main sector (the one with the highestreading) as well as each of the other sectors. In one implementation,the angle adjustment from the main sector azimuth angle is based on aratio of the main sector interference power level to each of theremaining sector power levels, which may be referred to as the intensityratio for each of the remaining sectors.

Using the sector example of FIG. 10 , assume that for PRB 40 underanalysis, sector 1000-2 is the main sector and has an azimuth of 0° anda beam width of 120° and an interference power level of −83 dB, sector1000-3 has an interference power level of −102 dB, and sector 1000-1 hasan interference power level of −90 dB. Using this information, anintensity ratio of 1.23 is calculated for sector 1000-3 (−102/083) andan intensity ratio of 1.08 is calculated for sector 1000-1 (−90/−83).The angle of adjustment (denoted as θ in FIG. 10 ) may be calculatedusing the difference between the intensity ratios for sectors 1000-3 and1000-1, which is 0.15 in this case (1.23-1.08). This difference inratios is then multiplied with beam width of main sector 1000-2 (120°),resulting in an angle adjustment of 18° (120×0.15) toward sector 1000-1,as represented by adjusted vector 1050 in FIG. 10 . Note that if sector1000-3 had a higher intensity ratio than sector 1000-1, the differencewould be negative 0.15, which would result in a −18° angle adjustmenttoward sector 1000-3.

Once the sector analysis vectors have been adjusted for all wirelessstations experiencing interference effects, the vectors may be applied(e.g., overlaid) on the heat map and/or cluster map to help target alikely interference source from among a number of candidate locations orclusters (block 1130).

The foregoing description of implementations provides illustration anddescription but is not intended to be exhaustive or to limit theinvention to the precise form disclosed. Modifications and variationsare possible in light of the above teachings or may be acquired frompractice of the invention. For example, while series of blocks andsignal messages have been described with respect to FIGS. 5 and 7 , theorder of the blocks and signal messages may be varied in otherimplementations. Moreover, non-dependent blocks may be performed inparallel.

Certain features described above may be implemented as “logic” or a“unit” that performs one or more functions. This logic or unit mayinclude hardware, such as one or more processors, microprocessors,application specific integrated circuits, or field programmable gatearrays, software, or a combination of hardware and software.

No element, act, or instruction used in the description of the presentapplication should be construed as critical or essential to theinvention unless explicitly described as such. Also, as used herein, thearticle “a” is intended to include one or more items. Further, thephrase “based on” is intended to mean “based, at least in part, on”unless explicitly stated otherwise.

To the extent the aforementioned embodiments collect, store, or employpersonal information of individuals, it should be understood that suchinformation shall be collected, stored, and used in accordance with allapplicable laws concerning protection of personal information.Additionally, the collection, storage, and use of such information canbe subject to consent of the individual to such activity, for example,through well known “opt-in” or “opt-out” processes as can be appropriatefor the situation and type of information. Storage and use of personalinformation can be in an appropriately secure manner reflective of thetype of information, for example, through various encryption andanonymization techniques for particularly sensitive information.

In the preceding specification, various preferred embodiments have beendescribed with reference to the accompanying drawings. It will, however,be evident that various modifications and changes may be made thereto,and additional embodiments may be implemented, without departing fromthe broader scope of the invention as set forth in the claims thatfollow. The specification and drawings are accordingly to be regarded inan illustrative rather than restrictive sense.

What is claimed is:
 1. A method, comprising: identifying a firstwireless station that has experienced radio frequency (RF) interferencefrom an unknown source on at least one physical resource block (PRB);identifying one or more second wireless stations that have experiencedsimilar interference on the at least one PRB; determining a plurality ofestimated interference source geographic locations based on at leastgeographic locations of the first wireless station and the one or moresecond wireless stations; scoring the plurality of estimatedinterference source geographic locations based on a comparison ofestimated interference to observed interference at the one or moresecond wireless stations; and generating a geographical map based on thescored plurality of estimated interference source geographic locations,wherein the geographical map includes indicia indicative of the relativescores of the plurality of estimated interference source geographiclocations.
 2. The method of claim 1, wherein identifying the firstwireless station comprises determining that a key performance indicator(KPI) for the at least one PRB on the first wireless station has a valueindicative of interference.
 3. The method of claim 2, wherein the KPIcomprises at least an uplink signal power level.
 4. The method of claim2, wherein identifying the one or more second wireless stationscomprises: identifying neighboring wireless stations proximate to thefirst wireless station based on respective geographic locations, andidentifying the one or more second wireless stations by comparing actualKPI values for the at least one PRB for each of the neighboring wirelessstations proximate to the first wireless station.
 5. The method of claim4, wherein determining the plurality of estimated interference sourcegeographic locations comprises: generating a boundary based on thegeographic locations of the first wireless station and the one or moresecond wireless stations; selecting a plurality of interference sourceestimated locations within the boundary; calculating expected KPI valuesfor each of the first and one or more second wireless stations based onthe plurality of interference source estimated geographic locations; anddetermining an accuracy associated with each of the plurality ofinterference source estimated geographic locations based on thecalculated expected KPI values and the actual KPI values.
 6. The methodof claim 5, wherein calculating the expected KPI values for each of thefirst and one or more second wireless stations based on the plurality ofinterference source estimated geographic locations comprises:calculating an estimated free space path loss for each of the first andone or more second wireless stations and for each of the plurality ofinterference source estimated geographic locations; and calculating theexpected KPI values based on the estimated free space path loss.
 7. Themethod of claim 6, further comprising: adjusting the expected KPI valuesbased on a sector of a respective wireless station experienced theinterference.
 8. The method of claim 5, wherein determining the accuracyassociated with each of the plurality of interference source estimatedgeographic locations further comprises calculating an error for each ofthe plurality of interference source estimated geographic locations. 9.The method of claim 8, wherein selecting the plurality of interferencesource estimated geographic locations within the boundary furthercomprises: performing minimization processing on the error.
 10. Themethod of claim 8, wherein scoring the plurality of estimatedinterference source geographic locations comprises: scoring theplurality of estimated interference source geographic locations based atleast on the error calculations.
 11. The method of claim 10, wherein theerror comprises a Root Mean Square Error (RMSE) and scoring is based onthe RMSE calculations and a count of the second wireless stations. 12.The method of claim 1, further comprising: providing the geographicalmap to field personnel for use in ascertaining the source of the RFinterference.
 13. The method of claim 1, wherein at least one of thefirst wireless station or the one or more second wireless stationsfurther comprise a plurality of sectors experiencing interference on theat least one PRB, wherein the method further comprises: determining amain sector based on the observed interference on each of the pluralityof sectors; determining an initial vector for each of the one or moresecond wireless stations having the plurality of sectors experiencinginterference based on the main sector; and adjusting an angle of theinitial vector based on the observed interference levels on theplurality of sectors to generate an adjusted vector, wherein theadjusted vector indicates a direction of a likely source ofinterference.
 14. A network device, comprising: a communicationinterface configured to: receive performance and location informationregarding a plurality of wireless stations; and a processor configuredto: identify a first wireless station in the plurality of wirelessstations that has experienced radio frequency (RF) interference from anunknown source on at least one physical resource block (PRB); identifyone or more second wireless stations in the plurality of wirelessstations that have experienced similar interference on the at least onePRB; determine a plurality of estimated interference source geographiclocations based on at least geographic locations of the first wirelessstation and the one or more second wireless stations; score theplurality of estimated interference source geographic locations based ona comparison of estimated interference to observed interference at theone or more second wireless stations; and generate a geographical mapbased on the scored plurality of estimated interference sourcegeographic locations, wherein the geographical map includes indiciaindicative of the relative scores of the plurality of estimatedinterference source geographic locations.
 15. The network device ofclaim 14, wherein the processor configured to identify the firstwireless station is configured to: determine that a key performanceindicator (KPI) for the least one physical resource block (PRB) on thefirst wireless station has a value indicative of interference, whereinthe KPI comprises at least an uplink signal power level.
 16. The networkdevice of claim 15, wherein the processor configured to identify one ormore second wireless stations is configured to: identify neighboringwireless stations proximate to the first wireless station based onrespective geographic locations, and identify the one or more secondwireless stations by comparing actual KPI values for the at least onePRB for each of the neighboring wireless stations proximate to the firstwireless station.
 17. The network device of claim 16, wherein theprocessor configured to determine a plurality of estimated interferencesource geographic locations is further configured to: generate aboundary based on the geographic locations of the first wireless stationand the one or more second wireless stations; select a plurality ofinterference source estimated geographic locations within the boundary;calculate expected KPI values for each of the first and one or moresecond wireless stations based on the plurality of interference sourceestimated geographic locations; and determine an accuracy associatedwith each of the plurality of interference source estimated geographiclocations based on the calculated expected KPI values and the actual KPIvalues.
 18. The network device of claim 17, wherein the processorconfigured to calculate expected KPI values for each of the first andone or more second wireless stations based on the plurality ofinterference source estimated geographic locations is further configuredto: calculate an estimated free space path loss for each of the firstand one or more second wireless stations and for each of the pluralityof interference source estimated geographic locations; and calculate theexpected KPI values based on the estimated free space path loss.
 19. Thenetwork device of claim 17, wherein the processor configured todetermine the accuracy associated with each of the plurality ofinterference source estimated geographic locations is configured to:calculate a root mean square error (RMSE) for each of the plurality ofinterference source estimated geographic locations.
 20. A non-transitorystorage medium storing instructions executable by a network device,wherein the instructions comprise instructions to cause the networkdevice to: identify a first wireless station in a plurality of wirelessstations that has experienced radio frequency (RF) interference from anunknown source on at least one physical resource block (PRB); identifyone or more second wireless stations in the plurality of wirelessstations that have experienced similar interference on the at least onePRB; determine a plurality of estimated interference source geographiclocations based on at least geographic locations of the first wirelessstation and the one or more second wireless stations; score theplurality of estimated interference source geographic locations based ona comparison of an estimated interference to observed interference atthe one or more second wireless stations; and generate a geographicalmap based on the scored plurality of estimated interference sourcegeographic locations, wherein the geographical map includes indiciaindicative of the relative scores of the plurality of estimatedinterference source geographic locations.